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2 Commits
4b6ee4af09
...
3c2db523ac
| Author | SHA1 | Date |
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 Pierre-Antoine
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3c2db523ac | |
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Pierre-Antoine
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9bb02edee4 |
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@ -1168,131 +1168,225 @@ class SedimentCalibrationTab(QWidget):
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self.fig_BS.canvas.draw_idle()
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self.fig_BS.canvas.draw_idle()
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def sample_choice_for_calibration(self):
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def sample_choice_for_calibration(self):
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fine_id = self.combobox_fine_sample_choice.currentIndexes()
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fine_data = self.combobox_fine_sample_choice.currentData()
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sand_id = self.combobox_sand_sample_choice.currentIndex()
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sand_data = self.combobox_sand_sample_choice.currentData()
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sand_text = self.combobox_sand_sample_choice.currentText()
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# --- List selected fine samples ---
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# --- List selected fine samples ---
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stg.fine_sample_profile = [(f, int(f[1:]) - 1) for f in self.combobox_fine_sample_choice.currentData()]
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stg.fine_sample_profile = [
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stg.calib_fine_profiles = self.combobox_fine_sample_choice.currentIndexes()
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(f, int(f[1:]) - 1) for f in fine_data
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]
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stg.calib_fine_profiles = fine_id
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# --- List selected sand samples ---
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# --- List selected sand samples ---
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# stg.sand_sample_target = [(s, int(s[1:]) - 1) for s in self.combobox_sand_sample_choice.currentData()]
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stg.sand_sample_target = [(sand_text, sand_id)]
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stg.sand_sample_target = [(self.combobox_sand_sample_choice.currentText(),
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stg.calib_sand_target = sand_id
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self.combobox_sand_sample_choice.currentIndex())]
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stg.calib_sand_target = self.combobox_sand_sample_choice.currentIndex()
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# --- Find index in time (along acoustic recording) of sand sample target ---
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t1, t2 = self.sample_choice_for_calibration_times()
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if stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
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d1, d2 = self.sample_choice_for_calibration_depths()
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t1 = (
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np.where(np.abs(stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()][
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self.combobox_freq1.currentIndex()] - stg.time_sand[stg.sand_sample_target[0][1]]) ==
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np.nanmin(np.abs(stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()][
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self.combobox_freq1.currentIndex()] - stg.time_sand[stg.sand_sample_target[0][1]])))[0][0]
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)
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t2 = (
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np.where(np.abs(stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()][
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self.combobox_freq2.currentIndex()] - stg.time_sand[stg.sand_sample_target[0][1]]) ==
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np.nanmin(np.abs(stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()][
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self.combobox_freq2.currentIndex()] - stg.time_sand[stg.sand_sample_target[0][1]])))[0][0]
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)
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else:
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t1 = (
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np.where(np.abs(stg.time[self.combobox_acoustic_data_choice.currentIndex()][
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self.combobox_freq1.currentIndex()] - stg.time_sand[
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stg.sand_sample_target[0][1]]) ==
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np.nanmin(np.abs(stg.time[self.combobox_acoustic_data_choice.currentIndex()][
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self.combobox_freq1.currentIndex()] - stg.time_sand[
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stg.sand_sample_target[0][1]])))[0][0]
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)
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t2 = (
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np.where(np.abs(stg.time[self.combobox_acoustic_data_choice.currentIndex()][
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self.combobox_freq2.currentIndex()] - stg.time_sand[
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stg.sand_sample_target[0][1]]) ==
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np.nanmin(np.abs(stg.time[self.combobox_acoustic_data_choice.currentIndex()][
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self.combobox_freq2.currentIndex()] - stg.time_sand[
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stg.sand_sample_target[0][1]])))[0][0]
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)
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# --- Find index in depth (along acoustic recording) of sand sample target ---
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if stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
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d1 = (
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np.where(np.abs(stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()][
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self.combobox_freq1.currentIndex()] - (-stg.depth_sand[stg.sand_sample_target[0][1]]) ) ==
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np.nanmin(np.abs(stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()][
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self.combobox_freq1.currentIndex()] - (-stg.depth_sand[stg.sand_sample_target[0][1]]) )))[0][0]
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)
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d2 = (
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np.where(np.abs(stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()][
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self.combobox_freq2.currentIndex()] - (-stg.depth_sand[stg.sand_sample_target[0][1]]) ) ==
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np.nanmin(np.abs(stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()][
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self.combobox_freq2.currentIndex()] - (-stg.depth_sand[stg.sand_sample_target[0][1]]) )))[0][0]
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)
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else:
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d1 = (
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np.where(np.abs(stg.depth[self.combobox_acoustic_data_choice.currentIndex()][
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self.combobox_freq1.currentIndex()] - (-stg.depth_sand[
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stg.sand_sample_target[0][1]]) ) ==
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np.nanmin(np.abs(stg.depth[self.combobox_acoustic_data_choice.currentIndex()][
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self.combobox_freq1.currentIndex()] - (-stg.depth_sand[
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stg.sand_sample_target[0][1]]) )))[0][0]
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)
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d2 = (
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np.where(np.abs(stg.depth[self.combobox_acoustic_data_choice.currentIndex()][
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self.combobox_freq2.currentIndex()] - (-stg.depth_sand[
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stg.sand_sample_target[0][1]]) ) ==
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np.nanmin(np.abs(stg.depth[self.combobox_acoustic_data_choice.currentIndex()][
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self.combobox_freq2.currentIndex()] - (-stg.depth_sand[
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stg.sand_sample_target[0][1]]) )))[0][0]
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)
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stg.sand_sample_target_indice = [(d1, t1), (d2, t2)]
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stg.sand_sample_target_indice = [(d1, t1), (d2, t2)]
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def summary_samples_choices(self):
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def sample_choice_for_calibration_times(self):
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data_id = self.combobox_acoustic_data_choice.currentIndex()
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self.pushbutton_compute_calibration.setToolTip("Calibration is computed at abscissa " + str(self.combobox_sand_sample_choice.currentText()))
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freq1_id = self.combobox_freq1.currentIndex()
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freq2_id = self.combobox_freq1.currentIndex()
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# --- Find index in time (along acoustic recording) of sand sample target ---
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if stg.time_cross_section[data_id].shape != (0,):
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time_data = stg.time_cross_section
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else:
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time_data = stg.time
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t1 = (
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np.where(
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np.abs(
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time_data[data_id][freq1_id]
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- stg.time_sand[stg.sand_sample_target[0][1]]
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) == np.nanmin(
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np.abs(
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time_data[data_id][freq1_id]
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- stg.time_sand[stg.sand_sample_target[0][1]]
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)
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)
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)[0][0]
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)
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t2 = (
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np.where(
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np.abs(
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time_data[data_id][freq2_id]
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- stg.time_sand[stg.sand_sample_target[0][1]]
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) == np.nanmin(
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np.abs(
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time_data[data_id][freq2_id]
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- stg.time_sand[stg.sand_sample_target[0][1]]
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)
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)
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)[0][0]
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)
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return (t1, t2)
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def sample_choice_for_calibration_depths(self):
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data_id = self.combobox_acoustic_data_choice.currentIndex()
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freq1_id = self.combobox_freq1.currentIndex()
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freq2_id = self.combobox_freq2.currentIndex()
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# --- Find index in depth (along acoustic recording) of sand sample target ---
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if stg.depth_cross_section[data_id].shape != (0,):
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depth_data = stg.depth_cross_section
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else:
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depth_data = stg.depth
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d1 = (
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np.where(
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np.abs(
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depth_data[data_id][freq1_id]
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- (-stg.depth_sand[stg.sand_sample_target[0][1]])
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) == np.nanmin(
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np.abs(
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depth_data[data_id][freq1_id] -
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(-stg.depth_sand[stg.sand_sample_target[0][1]])
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)
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)
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)[0][0]
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)
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d2 = (
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np.where(
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np.abs(
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depth_data[data_id][freq2_id]
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- (-stg.depth_sand[stg.sand_sample_target[0][1]])
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) == np.nanmin(
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np.abs(
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depth_data[data_id][freq2_id]
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- (-stg.depth_sand[stg.sand_sample_target[0][1]])
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)
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)
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)[0][0]
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)
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return (d1, d2)
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def summary_samples_choices(self):
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self.pushbutton_compute_calibration\
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.setToolTip(
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"Calibration is computed at abscissa "
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+ str(self.combobox_sand_sample_choice.currentText())
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)
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for i in reversed(range(self.gridLayout_groupbox_interpolate_info.count())):
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for i in reversed(range(self.gridLayout_groupbox_interpolate_info.count())):
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self.gridLayout_groupbox_interpolate_info.itemAt(i).widget().setParent(None)
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self.gridLayout_groupbox_interpolate_info\
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.itemAt(i)\
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.widget()\
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.setParent(None)
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self.gridLayout_groupbox_interpolate_info.addWidget(self.pushbutton_interpolate_Mfine_profile, 0, 0, 1, 4, Qt.AlignCenter)
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self.gridLayout_groupbox_interpolate_info\
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.addWidget(
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self.pushbutton_interpolate_Mfine_profile,
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0, 0, 1, 4,
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Qt.AlignCenter
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)
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self.summary_samples_choices_fine()
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self.summary_samples_choices_sand()
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def summary_samples_choices_fine(self):
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fine_head = ["Sample", "Depth (m)", "time", "Cfine (g/L)"]
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fine_head = ["Sample", "Depth (m)", "time", "Cfine (g/L)"]
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fine_label = [self.label_sample_fine, self.label_depth_fine, self.label_time_fine,
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fine_label = [
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self.label_concentration_fine]
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self.label_sample_fine,
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self.label_depth_fine,
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self.label_time_fine,
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self.label_concentration_fine
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]
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for j in range(len(fine_head)):
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for j in range(len(fine_head)):
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exec("fine_label[" + str(j) + "] = QLabel()")
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fine_label[j] = QLabel()
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eval("fine_label[" + str(j) + "].setText(fine_head[" + str(j) + "])")
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fine_label[j].setText(fine_head[j])
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print((f"self.gridLayout_groupbox_interpolate_info.addWidget(fine_label[{j}], 1, {j}, 1, 1, Qt.AlignCenter)"))
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self.gridLayout_groupbox_interpolate_info\
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eval(f"self.gridLayout_groupbox_interpolate_info.addWidget(fine_label[{j}], 1, {j}, 1, 1, Qt.AlignCenter)")
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.addWidget(
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fine_label[j], 1, j, 1, 1, Qt.AlignCenter
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)
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self.gridLayout_groupbox_interpolate_info\
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.addWidget(
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fine_label[j], 1, j, 1, 1, Qt.AlignCenter
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)
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fine_data = []
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fine_data = []
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for k in range(len(stg.fine_sample_profile)):
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for k in range(len(stg.fine_sample_profile)):
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fine_data.append([stg.fine_sample_profile[k][0], str(stg.depth_fine[k]), str(stg.time_fine[k]), str(stg.Ctot_fine[k])])
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fine_data.append(
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print(fine_data)
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[
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stg.fine_sample_profile[k][0],
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str(stg.depth_fine[k]),
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str(stg.time_fine[k]),
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str(stg.Ctot_fine[k])
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]
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)
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for p in range(len(fine_data)):
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for p in range(len(fine_data)):
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for q in range(len(fine_data[0])):
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for q in range(len(fine_data[0])):
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print(f"self.gridLayout_groupbox_interpolate_info.addWidget(QLabel(fine_data[{p}][{q}]), {2 + p}, {q}, 1, 1, Qt.AlignCenter)")
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self.gridLayout_groupbox_interpolate_info\
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eval(f"self.gridLayout_groupbox_interpolate_info.addWidget(QLabel(fine_data[{p}][{q}]), {2 + p}, {q}, 1, 1, Qt.AlignCenter)")
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.addWidget(
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QLabel(fine_data[p][q]),
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2 + p, q, 1, 1,
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Qt.AlignCenter
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)
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self.gridLayout_groupbox_interpolate_info.addWidget(self.double_horizontal_line, 2 + len(fine_data), 0, 1, 4, Qt.AlignCenter)
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self.gridLayout_groupbox_interpolate_info\
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.addWidget(
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self.double_horizontal_line,
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2 + len(fine_data), 0, 1, 4,
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Qt.AlignCenter
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)
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def summary_samples_choices_sand(self):
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sand_head = ["Sample", "Depth (m)", "time", "Csand (g/L)"]
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sand_head = ["Sample", "Depth (m)", "time", "Csand (g/L)"]
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sand_label = [self.label_sample_sand, self.label_depth_sand, self.label_time_sand,
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sand_label = [
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self.label_concentration_sand]
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self.label_sample_sand,
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self.label_depth_sand,
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self.label_time_sand,
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self.label_concentration_sand
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]
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fine_data = []
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for k in range(len(stg.fine_sample_profile)):
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fine_data.append(
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[
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stg.fine_sample_profile[k][0],
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str(stg.depth_fine[k]),
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str(stg.time_fine[k]),
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str(stg.Ctot_fine[k])
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]
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)
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for s in range(len(sand_head)):
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for s in range(len(sand_head)):
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exec("sand_label[" + str(s) + "] = QLabel()")
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sand_label[s] = QLabel()
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eval("sand_label[" + str(s) + "].setText(sand_head[" + str(s) + "])")
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sand_label[s].setText(sand_head[s])
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print(f"self.gridLayout_groupbox_interpolate_info.addWidget(sand_label[{s}], {3 + len(fine_data)}, {s}, 1, 1, Qt.AlignCenter)")
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self.gridLayout_groupbox_interpolate_info\
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eval(f"self.gridLayout_groupbox_interpolate_info.addWidget(sand_label[{s}], {3 + len(fine_data)}, {s}, 1, 1, Qt.AlignCenter)")
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.addWidget(
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sand_label[s],
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3 + len(fine_data), s, 1, 1,
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Qt.AlignCenter
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)
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sand_data = [stg.sand_sample_target[0][0],
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sand_data = [
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str(stg.depth_sand[stg.sand_sample_target[0][1]]),
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stg.sand_sample_target[0][0],
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str(stg.time_sand[stg.sand_sample_target[0][1]]),
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str(stg.depth_sand[stg.sand_sample_target[0][1]]),
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str(stg.Ctot_sand[stg.sand_sample_target[0][1]])]
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str(stg.time_sand[stg.sand_sample_target[0][1]]),
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str(stg.Ctot_sand[stg.sand_sample_target[0][1]])
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]
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for t in range(len(sand_data)):
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for t in range(len(sand_data)):
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self.gridLayout_groupbox_interpolate_info.addWidget(QLabel(sand_data[t]), 4 + len(fine_data), t, 1, 1, Qt.AlignCenter)
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self.gridLayout_groupbox_interpolate_info\
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.addWidget(
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QLabel(sand_data[t]),
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4 + len(fine_data), t, 1, 1,
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Qt.AlignCenter
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)
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|
|
||||||
def plot_profile_of_concentration_fine(self):
|
def plot_profile_of_concentration_fine(self):
|
||||||
|
|
||||||
|
|
@ -2177,302 +2271,239 @@ class SedimentCalibrationTab(QWidget):
|
||||||
stg.time[self.combobox_acoustic_data_choice.currentIndex()].shape[1], axis=2))
|
stg.time[self.combobox_acoustic_data_choice.currentIndex()].shape[1], axis=2))
|
||||||
|
|
||||||
def compute_FCB(self):
|
def compute_FCB(self):
|
||||||
|
data_id = self.combobox_acoustic_data_choice.currentIndex()
|
||||||
|
fcb_id = self.combobox_frequency_FCB.currentIndex()
|
||||||
|
|
||||||
self.combobox_frequency_FCB.clear()
|
self.combobox_frequency_FCB.clear()
|
||||||
self.combobox_frequency_FCB.addItems(stg.freq_text[self.combobox_acoustic_data_choice.currentIndex()])
|
self.combobox_frequency_FCB.addItems(stg.freq_text[data_id])
|
||||||
|
|
||||||
self.range_cells_function()
|
self.range_cells_function()
|
||||||
|
|
||||||
if stg.BS_stream_bed_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
|
BS_data = stg.BS_raw_data
|
||||||
|
|
||||||
stg.FCB = \
|
if stg.BS_stream_bed_pre_process_average[data_id].shape != (0,):
|
||||||
(np.log(stg.BS_stream_bed_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()]) +
|
BS_data = stg.BS_stream_bed_pre_process_average
|
||||||
np.log(stg.depth_real) +
|
elif stg.BS_stream_bed_pre_process_SNR[data_id].shape != (0,):
|
||||||
2 * stg.water_attenuation[self.combobox_acoustic_data_choice.currentIndex()][
|
BS_data = stg.BS_stream_bed_pre_process_SNR
|
||||||
self.combobox_frequency_FCB.currentIndex()] *
|
elif stg.BS_stream_bed[data_id].shape != (0,):
|
||||||
stg.depth_real)
|
BS_data = stg.BS_stream_bed
|
||||||
|
elif stg.BS_cross_section_pre_process_average[data_id].shape != (0,):
|
||||||
|
BS_data = stg.BS_cross_section_pre_process_average
|
||||||
|
elif stg.BS_cross_section_pre_process_SNR[data_id].shape != (0,):
|
||||||
|
BS_data = stg.BS_cross_section_pre_process_SNR
|
||||||
|
elif stg.BS_cross_section[data_id].shape != (0,):
|
||||||
|
BS_data = stg.BS_cross_section
|
||||||
|
elif stg.BS_raw_data_pre_process_average[data_id].shape != (0,):
|
||||||
|
BS_data = stg.BS_raw_data_pre_process_average
|
||||||
|
elif stg.BS_raw_data_pre_process_SNR[data_id].shape != (0,):
|
||||||
|
BS_data = stg.BS_raw_data_pre_process_SNR
|
||||||
|
|
||||||
elif stg.BS_stream_bed_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
|
stg.FCB = (
|
||||||
|
np.log(BS_data[data_id])
|
||||||
stg.FCB = \
|
+ np.log(stg.depth_real)
|
||||||
(np.log(stg.BS_stream_bed_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()]) +
|
+ 2 * stg.water_attenuation[data_id][fcb_id]
|
||||||
np.log(stg.depth_real) +
|
* stg.depth_real
|
||||||
2 * stg.water_attenuation[self.combobox_acoustic_data_choice.currentIndex()][
|
)
|
||||||
self.combobox_frequency_FCB.currentIndex()] *
|
|
||||||
stg.depth_real)
|
|
||||||
|
|
||||||
elif stg.BS_stream_bed[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
|
|
||||||
|
|
||||||
stg.FCB = \
|
|
||||||
(np.log(stg.BS_stream_bed[self.combobox_acoustic_data_choice.currentIndex()]) +
|
|
||||||
np.log(stg.depth_real) +
|
|
||||||
2 * stg.water_attenuation[self.combobox_acoustic_data_choice.currentIndex()][
|
|
||||||
self.combobox_frequency_FCB.currentIndex()] *
|
|
||||||
stg.depth_real)
|
|
||||||
|
|
||||||
elif stg.BS_cross_section_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
|
|
||||||
|
|
||||||
stg.FCB = \
|
|
||||||
(np.log(stg.BS_cross_section_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()]) +
|
|
||||||
np.log(stg.depth_real) +
|
|
||||||
2 * stg.water_attenuation[self.combobox_acoustic_data_choice.currentIndex()][
|
|
||||||
self.combobox_frequency_FCB.currentIndex()] *
|
|
||||||
stg.depth_real)
|
|
||||||
|
|
||||||
elif stg.BS_cross_section_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
|
|
||||||
|
|
||||||
stg.FCB = \
|
|
||||||
(np.log(stg.BS_cross_section_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()]) +
|
|
||||||
np.log(stg.depth_real) +
|
|
||||||
2 * stg.water_attenuation[self.combobox_acoustic_data_choice.currentIndex()][
|
|
||||||
self.combobox_frequency_FCB.currentIndex()] *
|
|
||||||
stg.depth_real)
|
|
||||||
|
|
||||||
elif stg.BS_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
|
|
||||||
|
|
||||||
stg.FCB = \
|
|
||||||
(np.log(stg.BS_cross_section[self.combobox_acoustic_data_choice.currentIndex()]) +
|
|
||||||
np.log(stg.depth_real) +
|
|
||||||
2 * stg.water_attenuation[self.combobox_acoustic_data_choice.currentIndex()][
|
|
||||||
self.combobox_frequency_FCB.currentIndex()] *
|
|
||||||
stg.depth_real)
|
|
||||||
|
|
||||||
elif stg.BS_raw_data_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
|
|
||||||
|
|
||||||
stg.FCB = \
|
|
||||||
(np.log(stg.BS_raw_data_pre_process_average[self.combobox_acoustic_data_choice.currentIndex()]) +
|
|
||||||
np.log(stg.depth_real) +
|
|
||||||
2 * stg.water_attenuation[self.combobox_acoustic_data_choice.currentIndex()][
|
|
||||||
self.combobox_frequency_FCB.currentIndex()] *
|
|
||||||
stg.depth_real)
|
|
||||||
|
|
||||||
elif stg.BS_raw_data_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
|
|
||||||
|
|
||||||
stg.FCB = \
|
|
||||||
(np.log(stg.BS_raw_data_pre_process_SNR[self.combobox_acoustic_data_choice.currentIndex()]) +
|
|
||||||
np.log(stg.depth_real) +
|
|
||||||
2 * stg.water_attenuation[self.combobox_acoustic_data_choice.currentIndex()][
|
|
||||||
self.combobox_frequency_FCB.currentIndex()] *
|
|
||||||
stg.depth_real)
|
|
||||||
|
|
||||||
elif stg.BS_raw_data[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
|
|
||||||
|
|
||||||
stg.FCB = \
|
|
||||||
(np.log(stg.BS_raw_data[self.combobox_acoustic_data_choice.currentIndex()]) +
|
|
||||||
np.log(stg.depth_real) +
|
|
||||||
2 * stg.water_attenuation[self.combobox_acoustic_data_choice.currentIndex()][
|
|
||||||
self.combobox_frequency_FCB.currentIndex()] *
|
|
||||||
stg.depth_real)
|
|
||||||
|
|
||||||
self.plot_FCB()
|
self.plot_FCB()
|
||||||
|
|
||||||
def plot_FCB(self):
|
def plot_FCB(self):
|
||||||
|
data_id = self.combobox_acoustic_data_choice.currentIndex()
|
||||||
|
fcb_id = self.combobox_frequency_FCB.currentIndex()
|
||||||
|
|
||||||
if stg.FCB.shape != (0,):
|
if stg.FCB.shape == (0,):
|
||||||
|
return
|
||||||
|
|
||||||
if stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
|
if stg.time_cross_section[data_id].shape != (0,):
|
||||||
|
self.slider_FCB.setMaximum(
|
||||||
|
stg.time_cross_section[data_id].shape[1]
|
||||||
|
)
|
||||||
|
else:
|
||||||
|
self.slider_FCB.setMaximum(stg.time[data_id].shape[1])
|
||||||
|
|
||||||
self.slider_FCB.setMaximum(stg.time_cross_section[
|
self.slider_FCB.setValue(stg.sand_sample_target_indice[0][1])
|
||||||
self.combobox_acoustic_data_choice.currentIndex()].shape[1])
|
|
||||||
|
|
||||||
else:
|
self.verticalLayout_groupbox_FCB_plot.removeWidget(self.canvas_FCB)
|
||||||
|
self.verticalLayout_groupbox_FCB_plot.removeWidget(self.toolbar_FCB)
|
||||||
|
|
||||||
self.slider_FCB.setMaximum(stg.time[self.combobox_acoustic_data_choice.currentIndex()].shape[1])
|
self.fig_FCB, self.axis_FCB = plt.subplots(
|
||||||
|
nrows=1, ncols=1, layout="constrained"
|
||||||
|
)
|
||||||
|
|
||||||
self.slider_FCB.setValue(stg.sand_sample_target_indice[0][1])
|
self.canvas_FCB = FigureCanvas(self.fig_FCB)
|
||||||
|
self.toolbar_FCB = NavigationToolBar(self.canvas_FCB, self)
|
||||||
|
|
||||||
self.verticalLayout_groupbox_FCB_plot.removeWidget(self.canvas_FCB)
|
self.verticalLayout_groupbox_FCB_plot.addWidget(self.toolbar_FCB)
|
||||||
self.verticalLayout_groupbox_FCB_plot.removeWidget(self.toolbar_FCB)
|
self.verticalLayout_groupbox_FCB_plot.addWidget(self.canvas_FCB)
|
||||||
|
|
||||||
self.fig_FCB, self.axis_FCB = plt.subplots(nrows=1, ncols=1, layout="constrained")
|
if stg.depth_cross_section[data_id].shape != (0,):
|
||||||
|
|
||||||
self.canvas_FCB = FigureCanvas(self.fig_FCB)
|
self.axis_FCB.plot(
|
||||||
self.toolbar_FCB = NavigationToolBar(self.canvas_FCB, self)
|
stg.depth_cross_section[data_id][fcb_id],
|
||||||
|
stg.FCB[fcb_id, :, self.slider_FCB.value() - 1],
|
||||||
|
linestyle="solid", linewidth=1, color="k"
|
||||||
|
)
|
||||||
|
else:
|
||||||
|
self.axis_FCB.plot(
|
||||||
|
stg.depth[data_id][fcb_id],
|
||||||
|
stg.FCB[fcb_id, :, self.slider_FCB.value() - 1],
|
||||||
|
linestyle="solid", linewidth=1, color="k"
|
||||||
|
)
|
||||||
|
|
||||||
self.verticalLayout_groupbox_FCB_plot.addWidget(self.toolbar_FCB)
|
self.axis_FCB.text(
|
||||||
self.verticalLayout_groupbox_FCB_plot.addWidget(self.canvas_FCB)
|
.95, .05,
|
||||||
|
stg.freq_text[data_id][fcb_id],
|
||||||
|
fontsize=10, fontweight='bold', fontname="DejaVu Sans",
|
||||||
|
fontstyle="normal", c="black", alpha=0.2,
|
||||||
|
horizontalalignment='right', verticalalignment='bottom',
|
||||||
|
transform=self.axis_FCB.transAxes
|
||||||
|
)
|
||||||
|
|
||||||
if stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
|
self.fig_FCB.supxlabel("Depth (m)")
|
||||||
|
self.fig_FCB.supylabel("FCB")
|
||||||
|
self.fig_FCB.canvas.draw_idle()
|
||||||
|
|
||||||
self.axis_FCB.plot(
|
self.slider_FCB.valueChanged.connect(self.update_plot_FCB)
|
||||||
stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()][
|
self.combobox_frequency_FCB.currentIndexChanged\
|
||||||
self.combobox_frequency_FCB.currentIndex()],
|
.connect(self.update_plot_FCB)
|
||||||
stg.FCB[self.combobox_frequency_FCB.currentIndex(), :, self.slider_FCB.value() - 1],
|
|
||||||
linestyle="solid", linewidth=1, color="k")
|
|
||||||
else:
|
|
||||||
|
|
||||||
self.axis_FCB.plot(
|
|
||||||
stg.depth[self.combobox_acoustic_data_choice.currentIndex()][
|
|
||||||
self.combobox_frequency_FCB.currentIndex()],
|
|
||||||
stg.FCB[self.combobox_frequency_FCB.currentIndex(), :, self.slider_FCB.value() - 1],
|
|
||||||
linestyle="solid", linewidth=1, color="k")
|
|
||||||
|
|
||||||
self.axis_FCB.text(.95, .05,
|
|
||||||
stg.freq_text[self.combobox_acoustic_data_choice.currentIndex()][
|
|
||||||
self.combobox_frequency_FCB.currentIndex()],
|
|
||||||
fontsize=10, fontweight='bold', fontname="DejaVu Sans",
|
|
||||||
fontstyle="normal", c="black", alpha=0.2,
|
|
||||||
horizontalalignment='right', verticalalignment='bottom',
|
|
||||||
transform=self.axis_FCB.transAxes)
|
|
||||||
|
|
||||||
self.fig_FCB.supxlabel("Depth (m)")
|
|
||||||
self.fig_FCB.supylabel("FCB")
|
|
||||||
self.fig_FCB.canvas.draw_idle()
|
|
||||||
|
|
||||||
self.slider_FCB.valueChanged.connect(self.update_plot_FCB)
|
|
||||||
self.combobox_frequency_FCB.currentIndexChanged.connect(self.update_plot_FCB)
|
|
||||||
|
|
||||||
def update_plot_FCB(self):
|
def update_plot_FCB(self):
|
||||||
|
data_id = self.combobox_acoustic_data_choice.currentIndex()
|
||||||
|
fcb_id = self.combobox_frequency_FCB.currentIndex()
|
||||||
|
|
||||||
|
freq1_id = self.combobox_freq1.currentIndex()
|
||||||
|
freq2_id = self.combobox_freq2.currentIndex()
|
||||||
|
|
||||||
if stg.FCB.shape != (0,):
|
if stg.FCB.shape != (0,):
|
||||||
self.axis_FCB.cla()
|
self.axis_FCB.cla()
|
||||||
|
|
||||||
if stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
|
if stg.depth_cross_section[data_id].shape != (0,):
|
||||||
|
|
||||||
self.axis_FCB.plot(
|
self.axis_FCB.plot(
|
||||||
stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()][
|
stg.depth_cross_section[data_id][fcb_id],
|
||||||
self.combobox_frequency_FCB.currentIndex()],
|
stg.FCB[fcb_id, :, self.slider_FCB.value() - 1],
|
||||||
stg.FCB[self.combobox_frequency_FCB.currentIndex(), :, self.slider_FCB.value() - 1],
|
linestyle="solid", linewidth=1, color="k"
|
||||||
linestyle="solid", linewidth=1, color="k")
|
)
|
||||||
|
|
||||||
else:
|
else:
|
||||||
|
|
||||||
self.axis_FCB.plot(
|
self.axis_FCB.plot(
|
||||||
stg.depth[self.combobox_acoustic_data_choice.currentIndex()][
|
stg.depth[data_id][fcb_id],
|
||||||
self.combobox_frequency_FCB.currentIndex()],
|
stg.FCB[fcb_id, :, self.slider_FCB.value() - 1],
|
||||||
stg.FCB[self.combobox_frequency_FCB.currentIndex(), :, self.slider_FCB.value() - 1],
|
linestyle="solid", linewidth=1, color="k"
|
||||||
linestyle="solid", linewidth=1, color="k")
|
)
|
||||||
|
|
||||||
self.axis_FCB.text(.95, .05,
|
self.axis_FCB.text(
|
||||||
stg.freq_text[self.combobox_acoustic_data_choice.currentIndex()][
|
.95, .05,
|
||||||
self.combobox_frequency_FCB.currentIndex()],
|
stg.freq_text[data_id][fcb_id],
|
||||||
fontsize=10, fontweight='bold', fontname="DejaVu Sans",
|
fontsize=10, fontweight='bold', fontname="DejaVu Sans",
|
||||||
fontstyle="normal", c="black", alpha=0.2,
|
fontstyle="normal", c="black", alpha=0.2,
|
||||||
horizontalalignment='right', verticalalignment='bottom',
|
horizontalalignment='right', verticalalignment='bottom',
|
||||||
transform=self.axis_FCB.transAxes)
|
transform=self.axis_FCB.transAxes
|
||||||
|
)
|
||||||
|
|
||||||
self.fig_FCB.canvas.draw_idle()
|
self.fig_FCB.canvas.draw_idle()
|
||||||
|
|
||||||
# --- Update red line on acoustic record plot ---
|
# --- Update red line on acoustic record plot ---
|
||||||
|
|
||||||
if stg.sand_sample_target_indice:
|
if stg.sand_sample_target_indice:
|
||||||
|
if stg.depth_cross_section[data_id].shape != (0,):
|
||||||
if stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
|
depth_data = stg.depth_cross_section
|
||||||
|
|
||||||
if stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
|
|
||||||
|
|
||||||
self.red_line_plot_return.set_data(
|
|
||||||
stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()][
|
|
||||||
self.combobox_freq2.currentIndex(), self.slider_FCB.value() -1] *
|
|
||||||
np.ones(
|
|
||||||
stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape[
|
|
||||||
1]),
|
|
||||||
-stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()][
|
|
||||||
self.combobox_freq2.currentIndex(), :])
|
|
||||||
|
|
||||||
else:
|
|
||||||
|
|
||||||
self.red_line_plot_return.set_data(
|
|
||||||
stg.time[self.combobox_acoustic_data_choice.currentIndex()][
|
|
||||||
self.combobox_freq2.currentIndex(), self.slider_FCB.value() -1] *
|
|
||||||
np.ones(stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape[
|
|
||||||
1]),
|
|
||||||
-stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()][
|
|
||||||
self.combobox_freq2.currentIndex(), :])
|
|
||||||
|
|
||||||
else:
|
else:
|
||||||
|
depth_data = stg.depth
|
||||||
|
|
||||||
if stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
|
if stg.time_cross_section[data_id].shape != (0,):
|
||||||
|
time_data = stg.time_cross_section
|
||||||
|
else:
|
||||||
|
time_data = stg.time
|
||||||
|
|
||||||
self.red_line_plot_return.set_data(
|
self.red_line_plot_return.set_data(
|
||||||
stg.time_cross_section[self.combobox_acoustic_data_choice.currentIndex()][
|
time_data[data_id][freq2_id, self.slider_FCB.value() -1]
|
||||||
self.combobox_freq2.currentIndex(), self.slider_FCB.value() -1] *
|
* np.ones(
|
||||||
np.ones(stg.depth[self.combobox_acoustic_data_choice.currentIndex()].shape[1]),
|
depth_data[data_id].shape[1]
|
||||||
-stg.depth[self.combobox_acoustic_data_choice.currentIndex()][
|
),
|
||||||
self.combobox_freq2.currentIndex(), :])
|
-stg.depth_data[data_id][freq2_id, :]
|
||||||
|
)
|
||||||
else:
|
|
||||||
|
|
||||||
self.red_line_plot_return.set_data(
|
|
||||||
stg.time[self.combobox_acoustic_data_choice.currentIndex()][
|
|
||||||
self.combobox_freq2.currentIndex(), self.slider_FCB.value() -1] *
|
|
||||||
np.ones(stg.depth[self.combobox_acoustic_data_choice.currentIndex()].shape[1]),
|
|
||||||
-stg.depth[self.combobox_acoustic_data_choice.currentIndex()][
|
|
||||||
self.combobox_freq2.currentIndex(), :])
|
|
||||||
|
|
||||||
self.fig_BS.canvas.draw_idle()
|
self.fig_BS.canvas.draw_idle()
|
||||||
|
|
||||||
def fit_FCB_profile_with_linear_regression_and_compute_alphaS(self):
|
def fit_FCB_profile_with_linear_regression_and_compute_alphaS(self):
|
||||||
|
data_id = self.combobox_acoustic_data_choice.currentIndex()
|
||||||
|
fcb_id = self.combobox_frequency_FCB.currentIndex()
|
||||||
|
|
||||||
self.update_plot_FCB()
|
self.update_plot_FCB()
|
||||||
|
|
||||||
if stg.FCB.shape != (0,):
|
if stg.FCB.shape == (0,):
|
||||||
|
return
|
||||||
|
|
||||||
# --- Identify FCB profile where value are not NaN ---
|
# --- Identify FCB profile where value are not NaN ---
|
||||||
y0 = stg.FCB[self.combobox_frequency_FCB.currentIndex(), :, self.slider_FCB.value() - 1]
|
y0 = stg.FCB[fcb_id, :, self.slider_FCB.value() - 1]
|
||||||
y = y0[np.where(np.isnan(y0) == False)]
|
y = y0[np.where(np.isnan(y0) == False)]
|
||||||
|
|
||||||
if stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()].shape != (0,):
|
if stg.depth_cross_section[data_id].shape != (0,):
|
||||||
|
depth_data = stg.depth_cross_section
|
||||||
|
else:
|
||||||
|
depth_data = stg.depth
|
||||||
|
|
||||||
# --- Select depth corresponding to the FCB profile where value are not NaN ---
|
# --- Select depth corresponding to the FCB profile where value are not NaN ---
|
||||||
x0 = stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()][
|
x0 = depth_data[data_id][fcb_id, :]
|
||||||
self.combobox_frequency_FCB.currentIndex(), :]
|
x = x0[np.where(np.isnan(y0) == False)]
|
||||||
x = x0[np.where(np.isnan(y0) == False)]
|
|
||||||
|
|
||||||
# --- Find the indices of the values between which the linear regression is fitted ---
|
# --- Find the indices of the values between which the linear regression is fitted ---
|
||||||
value1 = np.where(np.round(np.abs(x - float(self.lineEdit_FCB_from.text().replace(',','.'))), 2) ==
|
value1 = np.where(
|
||||||
np.min(np.round(np.abs(x - float(self.lineEdit_FCB_from.text().replace(',','.'))), 2)))[0][0]
|
np.round(
|
||||||
value2 = np.where(np.round(np.abs(x - float(self.lineEdit_FCB_to.text().replace(',', '.'))), 2) ==
|
np.abs(
|
||||||
np.min(np.round(np.abs(x - float(self.lineEdit_FCB_to.text().replace(',', '.'))), 2)))[0][0]
|
x - float(
|
||||||
|
self.lineEdit_FCB_from\
|
||||||
|
.text().replace(',','.')
|
||||||
|
)
|
||||||
|
), 2
|
||||||
|
) == np.min(
|
||||||
|
np.round(
|
||||||
|
np.abs(
|
||||||
|
x - float(
|
||||||
|
self.lineEdit_FCB_from.text().replace(',','.'))
|
||||||
|
), 2
|
||||||
|
)
|
||||||
|
)
|
||||||
|
)[0][0]
|
||||||
|
|
||||||
lin_reg_compute = linregress(x[value1:value2], y[value1:value2])
|
value2 = np.where(
|
||||||
|
np.round(
|
||||||
|
np.abs(
|
||||||
|
x - float(
|
||||||
|
self.lineEdit_FCB_to.text().replace(',', '.')
|
||||||
|
)
|
||||||
|
), 2
|
||||||
|
) == np.min(
|
||||||
|
np.round(
|
||||||
|
np.abs(
|
||||||
|
x - float(
|
||||||
|
self.lineEdit_FCB_to.text().replace(',', '.')
|
||||||
|
)
|
||||||
|
), 2
|
||||||
|
)
|
||||||
|
)
|
||||||
|
)[0][0]
|
||||||
|
|
||||||
stg.lin_reg.clear()
|
lin_reg_compute = linregress(x[value1:value2], y[value1:value2])
|
||||||
stg.lin_reg = [lin_reg_compute.slope, lin_reg_compute.intercept]
|
|
||||||
|
|
||||||
# --- Plot result of linear regression ---
|
stg.lin_reg.clear()
|
||||||
self.axis_FCB.plot(
|
stg.lin_reg = [lin_reg_compute.slope, lin_reg_compute.intercept]
|
||||||
stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()][
|
|
||||||
self.combobox_frequency_FCB.currentIndex(), value1:value2],
|
|
||||||
stg.lin_reg[0] *
|
|
||||||
stg.depth_cross_section[self.combobox_acoustic_data_choice.currentIndex()][
|
|
||||||
self.combobox_frequency_FCB.currentIndex(), value1:value2] +
|
|
||||||
stg.lin_reg[1],
|
|
||||||
linestyle="dashed", linewidth=1, color="b")
|
|
||||||
|
|
||||||
else:
|
# --- Plot result of linear regression ---
|
||||||
|
self.axis_FCB.plot(
|
||||||
|
depth_data[data_id][fcb_id, value1:value2],
|
||||||
|
stg.lin_reg[0]
|
||||||
|
* depth_data[data_id][fcb_id, value1:value2]
|
||||||
|
+ stg.lin_reg[1],
|
||||||
|
linestyle="dashed", linewidth=1, color="b"
|
||||||
|
)
|
||||||
|
|
||||||
# --- Select depth corresponding to the FCB profile where value are not NaN ---
|
self.fig_FCB.canvas.draw_idle()
|
||||||
x0 = stg.depth[self.combobox_acoustic_data_choice.currentIndex()][
|
|
||||||
self.combobox_frequency_FCB.currentIndex(), :]
|
|
||||||
x = x0[np.where(np.isnan(y0) == False)]
|
|
||||||
|
|
||||||
# --- Find the indices of the values between which the linear regression is fitted ---
|
# --- Display the value of alphaS compute with FCB ---
|
||||||
value1 = np.where(np.round(np.abs(x - float(self.lineEdit_FCB_from.text().replace(',','.'))), 2) ==
|
self.label_alphaS_FCB.clear()
|
||||||
np.min(np.round(np.abs(x - float(self.lineEdit_FCB_from.text().replace(',','.'))), 2)))[0][0]
|
self.label_alphaS_FCB.setText(
|
||||||
value2 = np.where(np.round(np.abs(x - float(self.lineEdit_FCB_to.text().replace(',', '.'))), 2) ==
|
f"α<sub>s</sub> = {-0.5*stg.lin_reg[0]:.4f} dB/m"
|
||||||
np.min(np.round(np.abs(x - float(self.lineEdit_FCB_to.text().replace(',', '.'))), 2)))[0][0]
|
)
|
||||||
|
|
||||||
lin_reg_compute = linregress(x[value1:value2], y[value1:value2])
|
|
||||||
|
|
||||||
stg.lin_reg.clear()
|
|
||||||
stg.lin_reg = [lin_reg_compute.slope, lin_reg_compute.intercept]
|
|
||||||
|
|
||||||
# --- Plot result of linear regression ---
|
|
||||||
self.axis_FCB.plot(
|
|
||||||
stg.depth[self.combobox_acoustic_data_choice.currentIndex()][
|
|
||||||
self.combobox_frequency_FCB.currentIndex(), value1:value2],
|
|
||||||
stg.lin_reg[0] *
|
|
||||||
stg.depth[self.combobox_acoustic_data_choice.currentIndex()][
|
|
||||||
self.combobox_frequency_FCB.currentIndex(), value1:value2] +
|
|
||||||
stg.lin_reg[1],
|
|
||||||
linestyle="dashed", linewidth=1, color="b")
|
|
||||||
|
|
||||||
self.fig_FCB.canvas.draw_idle()
|
|
||||||
|
|
||||||
# --- Display the value of alphaS compute with FCB ---
|
|
||||||
self.label_alphaS_FCB.clear()
|
|
||||||
self.label_alphaS_FCB.setText(f"α<sub>s</sub> = {-0.5*stg.lin_reg[0]:.4f} dB/m")
|
|
||||||
|
|
||||||
def slider_profile_number_to_begin_FCB(self):
|
def slider_profile_number_to_begin_FCB(self):
|
||||||
self.slider_FCB.setValue(int(self.slider_FCB.minimum()))
|
self.slider_FCB.setValue(int(self.slider_FCB.minimum()))
|
||||||
|
|
|
||||||
Loading…
Reference in New Issue